Large-Scale Environments of Successive Atmospheric River Events Leading to Compound Precipitation Extremes in California
Autor: | Meredith A. Fish, James M. Done, Daniel L. Swain, Anna M. Wilson, Allison C. Michaelis, Peter B. Gibson, F. Martin Ralph |
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Rok vydání: | 2022 |
Předmět: | |
Zdroj: | Journal of Climate. 35:1515-1536 |
ISSN: | 1520-0442 0894-8755 |
DOI: | 10.1175/jcli-d-21-0168.1 |
Popis: | Successive atmospheric river (AR) events—known as AR families—can result in prolonged and elevated hydrological impacts relative to single ARs due to the lack of recovery time between periods of precipitation. Despite the outsized societal impacts that often stem from AR families, the large-scale environments and mechanisms associated with these compound events remain poorly understood. In this work, a new reanalysis-based 39-yr catalog of 248 AR family events affecting California between 1981 and 2019 is introduced. Nearly all (94%) of the interannual variability in AR frequency is driven by AR family versus single events. Using k-means clustering on the 500-hPa geopotential height field, six distinct clusters of large-scale patterns associated with AR families are identified. Two clusters are of particular interest due to their strong relationship with phases of El Niño–Southern Oscillation (ENSO). One of these clusters is characterized by a strong ridge in the Bering Sea and Rossby wave propagation, most frequently occurs during La Niña and neutral ENSO years, and is associated with the highest cluster-average precipitation across California. The other cluster, characterized by a zonal elongation of lower geopotential heights across the Pacific basin and an extended North Pacific jet, most frequently occurs during El Niño years and is associated with lower cluster-average precipitation across California but with a longer duration. In contrast, single AR events do not show obvious clustering of spatial patterns. This difference suggests that the potential predictability of AR families may be enhanced relative to single AR events, especially on subseasonal to seasonal time scales. |
Databáze: | OpenAIRE |
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